Top Products, BigCommerce

Metrics type: Key Metrics • Category: Ecommerce Platform

At a glance

The top revenue-generating products in the period, ranked by total revenue. Almost every ecommerce store follows the 80/20 rule: 20% of products produce 80% of revenue. The top-N table identifies that 20%, and is the canonical input to: (a) merchandising priority (which products get hero placement), (b) inventory priority (which products must never go OOS), (c) marketing priority (which products get ad spend), (d) margin protection (which products warrant supplier negotiation), and (e) catalogue rationalisation (which products earn their shelf space).


What it counts	Total order-line revenue per product across the current 30-day period, ranked descending. Default top 20; configurable to top 10, 50, or 100. Includes all channels and all geographies unless filtered. Excludes refunded line items.
Sample type	Backend API data from BigCommerce order line items, refreshed on the standard data refresh.
Why top products matter	(1) Concentration risk: knowing whether revenue is concentrated in 5 SKUs (high risk if any go OOS) or distributed across 50 (resilient) drives operational priority. (2) Inventory protection: the top-100 must have aggressive low-stock thresholds and supplier escalation procedures. (3) Ad ROAS: the top-100 are the highest-confidence ad-spend allocation; they convert reliably and have known LTV. (4) Catalogue rationalisation: products outside the top-1,000 (in mid-size catalogues) typically earn back their carrying cost only marginally; this card validates which products are pulling weight.
Reading the value	(1) Top 5 should represent 20-40% of revenue (typical ecommerce concentration). (2) Top 100 should represent 70-85% of revenue. (3) If top 5 is more than 50%, the store is concentration-risk-heavy; an OOS event on a single bestseller is a 10%+ revenue drop. (4) Cross-reference `bc_revenue_by_brand` and `bc_revenue_by_category` to identify whether revenue is also concentrated by brand or category.
Currency	currency (per product), with rank and share-of-total.
Time window	`30D vsP`.
Alert trigger	n/a (ranking card; alerts live on per-product OOS or velocity-change cards).
Sentiment key	n/a (composition view).
Roles	owner, merchandising, marketing

Calculation

top_products = SELECT product_id, product_name,
                  SUM(order_items.line_total) AS revenue,
                  SUM(order_items.quantity) AS units_sold,
                  COUNT(DISTINCT order_id) AS orders_with_product
               FROM order_items
               JOIN orders ON orders.id = order_items.order_id
               WHERE orders.date_created IN [today - 30d, today)
                 AND orders.payment_status IN ('paid', 'captured', 'completed')
                 AND order_items.refunded = false
               GROUP BY product_id
               ORDER BY revenue DESC
               LIMIT 20

Worked example

A UK-based BigCommerce home-and-garden store, top products reading on Wednesday 15 May 26 (30D).

Rank	Product	Revenue	Units	Orders	% of total	vs P
1	Garden Hose 30m Premium	£42,800	412	401	7.8%	+14%
2	Patio Set Wicker 6-piece	£38,200	86	86	7.0%	-3%
3	BBQ Charcoal Pro	£31,400	240	224	5.7%	+28%
4	Garden Tool Set 12-piece	£24,600	318	295	4.5%	+6%
5	Outdoor Cushion Set	£21,800	412	380	4.0%	+9%
6	Lawn Fertiliser 25kg	£18,400	504	472	3.4%	+12%
7	Plant Pot Set Terracotta	£15,200	622	510	2.8%	+4%
8	Garden Hose 15m Standard	£14,400	308	290	2.6%	-8%
9	Decking Cleaner 5L	£13,800	280	268	2.5%	+18%
10	Patio Heater Gas	£12,400	31	31	2.3%	-12%
-	(Top 10 subtotal)	£233,000	-	-	42.4%	+6%
-	Top 11-100 subtotal	£198,400	-	-	36.1%	+2%
-	Top 101-1,000 subtotal	£92,800	-	-	16.9%	-4%
-	Long tail (rest)	£24,942	-	-	4.5%	-1%
-	Total	£549,142	-	2,103	100%	-6.3%

What the top-products reading is telling us:

Top 10 produce 42.4% of revenue; top 100 produce 78.5%. Classic ecommerce concentration, slightly less concentrated than the typical 80/20 (suggests a healthy long-tail catalogue), but still heavily anchored in the top tier.
Bestseller velocity matters more than absolute count. Garden Hose 30m at rank 1 sold 412 units (high velocity, low AOV); Patio Set Wicker at rank 2 sold 86 units (low velocity, high AOV). Both produce similar revenue, but their operational implications differ wildly:
- Garden Hose: high-velocity SKU. Must never go OOS. Set low-stock threshold at 50+ units. Supplier lead time matters enormously.
- Patio Set: low-velocity, high-AOV SKU. OOS less catastrophic per day, but each lost order is £444. Set higher per-product fulfilment SLA.
Inventory and ad spend prioritisation.
- Aggressive low-stock thresholds for top 100: bump from default 5 to 20-50 units depending on velocity.
- Ad spend allocation: allocate 70-80% of paid budget to top 100 SKUs (where conversion is highest and CAC most predictable).
- Supplier negotiations: the top 100 are the leverage points for cost reductions; even 2% off COGS on the top 100 is meaningful margin.
Concerning movements:
- Patio Heater Gas (-12% vs P): seasonal, patio heater demand drops as weather warms. Expected.
- Garden Hose 15m Standard (-8% vs P): cannibalised by the larger 30m variant (+14%). Likely a category mix shift, not a real loss; merchandise the 30m as the default.
- Patio Set Wicker (-3%): likely competitive shift; investigate competitor pricing.
Strong growth movements:
- BBQ Charcoal Pro (+28%): BBQ-season tailwind. Confirm inventory; promote in seasonal email.
- Decking Cleaner 5L (+18%): spring cleaning category. Cross-sell with other decking products.
Long-tail health. 4.5% from products outside the top 1,000. This is a healthy long-tail proportion, neither too dependent on bestsellers nor wasted on dead inventory. Stores below 2% long-tail proportion are highly bestseller-dependent (vulnerable); stores above 15% may be diluted with products that don’t earn their carrying cost.
Recommended actions:
- Confirm top 10 inventory levels, none should be at risk of OOS in next 14 days.
- Review competitor pricing on declining items (Patio Heater Gas, Garden Hose 15m Standard).
- Capitalise on growth items via email + paid media campaigns on BBQ Charcoal and Decking Cleaner.
- Quarterly catalogue rationalisation review for products in the bottom 1,000-by-revenue if they’re consuming inventory or marketing resources.

The diagnostic flow:

Read top 10; assess concentration risk.
Confirm inventory protection for top 100.
Identify movement vs prior period; investigate large changes.
Allocate marketing + supplier focus on the bestseller tier.
Periodic long-tail review for catalogue rationalisation.

Rapid-response playbook:

Time horizon	Action
First 1 hour	Read top 10. Confirm inventory levels.
First day	Investigate large movers (positive and negative).
First week	Adjust low-stock thresholds, ad spend allocation.
Quarterly	Catalogue rationalisation review.

Sibling cards merchants should reference together

Card	Why merchants reach for it
`bc_revenue_by_brand`	Brand-level revenue.
`bc_revenue_by_category`	Category-level revenue.
`bc_product_margin`	Per-product margin.
`bc_refunded_products`	Top refunded products (different from top revenue).
`bc_channel_top_products`	Top products per channel.

Reconciling against the vendor’s own dashboard

Where to look in BC: Analytics → Insights → Products → Top Products by Revenue; Reports → Sales by Product. Why our number may differ:

Reason	Direction	What to do
Bundle handling. BC may aggregate bundle children to the parent SKU; Vortex IQ may show line-level.	Variable	Confirm setting.
Refund handling. BC may show gross revenue (before refunds); Vortex IQ excludes refunded line items.	Vortex IQ lower	Match policy.
Time period. BC defaults to calendar; Vortex IQ uses 30-day rolling.	Variable	Match periods.
Cancelled orders. BC may include; Vortex IQ excludes.	BC higher	Match filter.

Cross-connector: complement with klaviyo.klv_segments_overview (which audiences buy each top product) for marketing ROI. Quick rule: confirm bundle handling and refund handling first.

Known limitations / merchant FAQs

Q: We have one product producing 30% of our revenue. Is that a problem? Concentration risk, yes. Single-product dependency means an OOS event, supplier failure, or quality issue on that one product can wipe 30% of revenue overnight. Mitigations: (a) aggressive inventory buffer + secondary supplier, (b) develop adjacent or substitute products to diversify, (c) ensure ad spend is not 100% concentrated on this single SKU. Q: How does this card differ from bc_revenue_by_brand or bc_revenue_by_category? This is per-SKU; brand and category are aggregations. The three together give the merchandising story: which specific SKUs drive revenue, which brands they belong to, which categories they sit in. Use all three for inventory, marketing, and supplier negotiation. Q: Bundle products, does the parent or the child SKU show up? Configurable. Default: line-level (children appear individually with their portion of the bundle revenue). Some merchants prefer the parent (the bundle is what was sold). Configure per profile. Q: We have a seasonal product that ranks #1 in summer and #500 in winter. How is the card useful? Read the trend column (vs P), large movement signals seasonality. For year-round merchandising decisions, use the longer-window views (90D or 365D rolling) rather than 30D. Vortex IQ provides both; the dashboard hero is 30D for operational pulse. Q: Some of our top products have negative margin. Is the card showing that? Not directly. This card is revenue-ranked. To see margin-ranked, use bc_product_margin. A product can rank top by revenue but be unprofitable (loss-leader, deep discount, COGS underestimate); cross-checking with margin is essential. Q: We use BC’s “preorder” feature for upcoming products. Are pre-order revenues counted here? If payment captures at pre-order time (typical), yes. The order is a paid order with the product attributed; it appears in the period’s top products. If payment is deferred to fulfilment, it appears in the period when payment captures. Q: How is this card affected by SKU consolidation (variants vs individual SKUs)? The card aggregates at the product level (parent), not variant. A blue and red variant of the same shirt count as one product entry. For variant-level decomposition, use bc_top_skus (if available) or BC’s native variant report. Q: Should we delete products outside the top 1,000? Generally no, long-tail revenue compounds. Even 0.01% per SKU × 4,000 long-tail SKUs is 40% of revenue collectively. The right action is catalogue hygiene (descriptions, images, SEO) for the long tail, plus quarterly review for products with truly zero recent revenue.

Tracked live in Vortex IQ Nerve Centre

Top Products is one of hundreds of KPI pulses Vortex IQ tracks across BigCommerce and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. Start for free or book a demo to see this metric running on your own data.

Get Started

The AI OS

At a glance

Calculation

Worked example

Sibling cards merchants should reference together

Reconciling against the vendor’s own dashboard

Known limitations / merchant FAQs

Tracked live in Vortex IQ Nerve Centre

​At a glance

​Calculation

​Worked example

​Sibling cards merchants should reference together

​Reconciling against the vendor’s own dashboard

​Known limitations / merchant FAQs

​Tracked live in Vortex IQ Nerve Centre

At a glance

Calculation

Worked example

Sibling cards merchants should reference together

Reconciling against the vendor’s own dashboard

Known limitations / merchant FAQs

Tracked live in Vortex IQ Nerve Centre